The increasing prevalence of antimicrobial-resistant pathogens is one of the greatest challenges in clinical medicine today. Current culture-based approaches typically require 2-3 days to produce a susceptibility profile. Thus, the choice of empirical antimicrobial therapy is based on the most likely causative species and the species' most recent cumulative antibiogram for the region or hospital. Unfortunately, the empirical treatment now leads to potential ‘drug-bug’ mismatches in up to 25% of prescriptions and it is estimated that up to 50% of antibiotics are used inappropriately (Antibiotic Resistance Threats in the United States of America. CDC Report 2013; and Tchesnokova et al., J. Clin. Microbiol. 2013 September; 51(9):2991-2999.). Rapid molecular tools have been explored as a way to refine this process by targeting the genetic markers of resistance (Kalashnikov et al., Lab Chip 2012; Romero-Gomez J. Infect. 2012; Koser et al., PLoS Pathog. 2012; 8:e1002824; and Schofield et al., J. Microbiol. Methods 2012; 90:80-82). However, resistance to the same drug within same species very often depends on presence (and proper expression) of a wide range of specific genes or mutant variants (Arias et al., N. Engl. J. Med. 2009; 360:439-443; and Chenia et al., J. Antimicrob. Chemother. 2006; 58:1274-1278). Thus, it still remains unfeasible to predict resistance and, especially, susceptibility to multiple clinically relevant antibiotics by a single test that is based on the gene markers approach. Therefore, there is an urgent need to introduce novel tests and approaches to improve near-patient empirical treatment decisions to lower the risks associated with inappropriate antimicrobial use.
The increasing prevalence of antimicrobial-resistant pathogens is one of the greatest challenges in clinical medicine today (Alanis, Arch. Med. Res. 36:697-705, 2005; and Spellberg et al., Clin. Infect. Dis. 46:155-164, 2008.). Since current culture-based approaches typically require 1.5-3 days to produce a susceptibility profile, the patient's treatment usually must begin before the provider knows whether the antibiotic is likely to work or the treatment will be optimal with respect to cost, duration, and/or antimicrobial spectrum. The choice of empirical antimicrobial therapy must be based on the type of infection, the most likely causative species, and the species' typical susceptibility profiles (Jenkins and Schuetz. Mayo Clin. Proc. 87:290-308, 2012; and Dellit et al., Clin. Infect. Dis. 44:159-177, 2007). However, preferred antibiotics now encounter potential ‘drug-bug’ mismatches in up to 25% of prescriptions (Tchesnokova et al., J. Clin. Microbiol. 51(9):2991-2999, September 2013) and it is estimated that up to 50% of antibiotics are used inappropriately. Thus, there is an urgent need to provide physicians with rapid antimicrobial assays that guide appropriate treatment decisions to minimize risks associated with inappropriate or ineffective antimicrobial use.
Urinary tract infections are the most common bacterial infections in women and are caused primarily by E. coli. E. coli is a leading bacterial pathogen that, in developed countries, causes mainly UTI and bloodstream infections, resulting in millions of infections and tens of thousands of deaths each year in the United States alone. Like most bacterial pathogens, E. coli is a clonal species, with the pathogenic strains belonging to a limited number of genetically related lineages (i.e., clonotypes). Although certain E. coli clonotypes are known to have distinctive antimicrobial susceptibility patterns, the use of clonotyping as a general predictive marker for antimicrobial susceptibility has not been introduced into clinical practice. The main reason for this is that the most-commonly used clonal typing methods, multilocus sequence typing (MLST) and pulsed-field gel electrophoresis (PFGE), are not suited for diagnostics purposes due to their high costs, slow turnaround, and low prognostic values.
Urinary tract infections are the most common bacterial infections in women and elders that are caused primarily by E. coli and, in USA, results in millions of infections and tens of thousands of deaths (mostly from urosepsis) each year (Foxman, Nat. Rev. Urol. 2010 Dec.; 7(12):653-60; and Russo and Johnson, 2003 Microbes Infect. 5:449-456.). Like most bacterial pathogens, E. coli is a clonal species, with the pathogenic strains belonging to a limited number of genetically related lineages (i.e., clonotypes) that have distinctive antimicrobial susceptibility patterns (Wright et al., 2013. Am. J. Infect. Control 41:33-38; Peterson et al., 2012. Infect Control Hosp. Epidemiol. 33:790-795; Wright et al., Infect. Control Hosp. Epidemiol. 32:635-640, 2011; Johnson et al., J. Infect. Dis. 207:919-928, 2013; Am. J. Infect. Control 38:350-353, 2010; and La Forgia Am. J. Infect. Control 38:259-263, 2010). However, the most-commonly used clonal typing methods, multilocus sequence typing (MLST) and pulsed-field gel electrophoresis (PFGE) are not suited for diagnostics purposes due to their high costs, slow turnaround, and low prognostic values.
Others have tried, without much success, to develop rapid molecular tools as a way to refine this process (Kalashnikov et al. Lab Chip 2012; Romero-Gomez et al., J. Infect. 2012; Koser et al., PLoS Pathog. 2012; 8:e1002824; and Schofield et al. J. Microbiol. Methods 90:80-82, 2012), but since a wide range of genes and point mutations can confer resistance to the same drug, even within same species (Arias and Murray, N. Engl. J. Med. 360:439-443, 2009; and Chenia et al. J. Antimicrob. Chemother. 2006; 58:1274-8, 2006), detection of the broad scope of resistance determinants in one test remains unfeasible for routine clinical diagnostics.
In any medical treatment center, such as a hospital emergency care facility, patients presenting with bacterial infections need urgent treatment so as to prevent and treat any infection before the patient becomes septic. However, the choice of treatment with an antibiotic will depend on whether the infecting bacterial organism is resistant or susceptible to a particular antibiotic. The answer to that question has historically been done by culturing the infecting organism on an agar plate and adding antibiotic-soaked paper to the surface of the agar. The information which antibiotic is resistant or not can be achieved in a few days. But the treating physician does not have a few days to wait to find the correct answer. Instead, the treating physician has to guess which antibiotic(s) will work and balance the likelihood of resistance with side effect profiles of each antibiotic. Therefore, there is a significant need in the art for a process and test kit that can rapidly (i.e., within an hour) provide a better prediction of treatment choice based on the specific clonal subspecies of bacteria causing a patient's infection. The present disclosure provides a test kit and process to address that need.
Multilocus sequence typing (MLST) is often based on sequencing 5-8 housekeeping loci in a bacterial chromosome to provide descriptions of the bacterial species present. However, even strains with identical MLST profiles (known as sequence types or STs) may possess distinct genotypes, which enable different eco- or pathotypic lifestyles. Multilocus sequence typing (MLST) is a method for characterizing relatedness of strains within bacterial species (Maiden et al., Proc. Natl. Acad. Sci. USA 95:3140-3145, 1998). Standardized MLST schemes have been established for human pathogens, including E. coli (Wirth et al., Mol. Microbiol. 60:1136-1151, 2006). Certain E. coli sequence types are epidemiologically associated with specific extra-intestinal syndromes, such as ST127 and ST73 with pyelonephritis (Johnson et al., J. Clin. Microbiol. 46:417-422, 2008; and Johnson et al. Microbes Infect. 8:1702-1713, 2006). Others have shown emerging antimicrobial resistance properties, such as ST69 with trimethoprim/sulfamethoxozole resistance (Manges et al., N. Engl. J. Med. 345:1007-1013, 2001) and ST131 with fluoroquinolone resistance and extended-spectrum beta-lactamase production (Nicolas-Chanione et al., J. Antimicrob. Chemother. 61, 273-281, 2008).